A high-resolution suitability index for solar farm location in complex landscapes

Thomas Finn; Paul McKenzie

doi:10.1016/j.renene.2020.05.121

A high-resolution suitability index for solar farm location in complex landscapes

Thomas Finn
, Paul McKenzie

School of Geography and Environmental Sciences

Research output: Contribution to journal › Article › peer-review

38 Citations (Scopus)

101 Downloads (Pure)

Abstract

The introduction of renewable energy legislation in the European Union aims to encourage development of utility-scale renewable energy sources. Site location is a key part of strategic planning for renewables such as solar energy and is hampered in complex landscapes due to high spatial heterogeneity. This heterogeneity needs to be accounted for and incorporated into decision-making processes. This study used high-resolution spatial data in a Geographic Information System (GIS) alongside Analytical Hierarchy Process (AHP) and Multi-Criteria Decision Making (MCDM) to determine the potential for large-scale solar developments using Northern Ireland as a case study. Criteria were analysed using a weighted sum overlay, with weights calculated using a pairwise comparison method. The resulting Suitability Index model defined the level of suitability for 10% of the region with 392km2 identified as very suitable. Two potential site size criteria were then defined, based on manually mapped extents of current solar developments that identified 462 potential sites. A validation exercise identified modelled potential sites had high coincidence with existing and planned solar developments in the study area. The methodology can be applied across regions with complex landscape and settlement patterns with high accuracy and can be utilised by policymakers or renewable energy developers to efficiently target potential utility-scale solar developments.

Original language	English
Pages (from-to)	520-533
Number of pages	14
Journal	Renewable Energy
Volume	158
Early online date	3 Jun 2020
DOIs	https://doi.org/10.1016/j.renene.2020.05.121
Publication status	Published (in print/issue) - 31 Oct 2020

Bibliographical note

Funding Information:
The authors would also like to thank the representative from Elgin Energy, for providing a local developer's perspective regarding site suitability and the representative from Land and Property Services (LPS), for highlighting relevant data from a policymaker viewpoint. Sentinel-2A/B scenes were sourced as open data from the European Space Agency (ESA) Copernicus Open Access Hub. LPS data are provided as part of the Northern Ireland Mapping Agreement (NIMA) of which Ulster University (UU) is a participant (NIMA S&LA 577.319). Other spatial data are licensed under the Open Government Licence v3.0. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Publisher Copyright:
© 2020 Elsevier Ltd

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Funding

Funding Information: The authors would also like to thank the representative from Elgin Energy, for providing a local developer's perspective regarding site suitability and the representative from Land and Property Services (LPS), for highlighting relevant data from a policymaker viewpoint. Sentinel-2A/B scenes were sourced as open data from the European Space Agency (ESA) Copernicus Open Access Hub. LPS data are provided as part of the Northern Ireland Mapping Agreement (NIMA) of which Ulster University (UU) is a participant (NIMA S&LA 577.319). Other spatial data are licensed under the Open Government Licence v3.0. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Publisher Copyright: © 2020 Elsevier Ltd Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Analytical hierarchy process
GIS
Multi-criteria decision making
Site selection
Solar

Access to Document

10.1016/j.renene.2020.05.121

AcceptedVersion_anonymous_submission_160420Author Accepted Manuscript, 2.48 MB

Cite this

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abstract = "The introduction of renewable energy legislation in the European Union aims to encourage development of utility-scale renewable energy sources. Site location is a key part of strategic planning for renewables such as solar energy and is hampered in complex landscapes due to high spatial heterogeneity. This heterogeneity needs to be accounted for and incorporated into decision-making processes. This study used high-resolution spatial data in a Geographic Information System (GIS) alongside Analytical Hierarchy Process (AHP) and Multi-Criteria Decision Making (MCDM) to determine the potential for large-scale solar developments using Northern Ireland as a case study. Criteria were analysed using a weighted sum overlay, with weights calculated using a pairwise comparison method. The resulting Suitability Index model defined the level of suitability for 10\% of the region with 392km2 identified as very suitable. Two potential site size criteria were then defined, based on manually mapped extents of current solar developments that identified 462 potential sites. A validation exercise identified modelled potential sites had high coincidence with existing and planned solar developments in the study area. The methodology can be applied across regions with complex landscape and settlement patterns with high accuracy and can be utilised by policymakers or renewable energy developers to efficiently target potential utility-scale solar developments.",

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N2 - The introduction of renewable energy legislation in the European Union aims to encourage development of utility-scale renewable energy sources. Site location is a key part of strategic planning for renewables such as solar energy and is hampered in complex landscapes due to high spatial heterogeneity. This heterogeneity needs to be accounted for and incorporated into decision-making processes. This study used high-resolution spatial data in a Geographic Information System (GIS) alongside Analytical Hierarchy Process (AHP) and Multi-Criteria Decision Making (MCDM) to determine the potential for large-scale solar developments using Northern Ireland as a case study. Criteria were analysed using a weighted sum overlay, with weights calculated using a pairwise comparison method. The resulting Suitability Index model defined the level of suitability for 10% of the region with 392km2 identified as very suitable. Two potential site size criteria were then defined, based on manually mapped extents of current solar developments that identified 462 potential sites. A validation exercise identified modelled potential sites had high coincidence with existing and planned solar developments in the study area. The methodology can be applied across regions with complex landscape and settlement patterns with high accuracy and can be utilised by policymakers or renewable energy developers to efficiently target potential utility-scale solar developments.

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A high-resolution suitability index for solar farm location in complex landscapes

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

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